Modeling of Neonatal Skull Development Using Computed Tomography Images

Accuracy of intravascular ultrasound-derived virtual fractional flow reserve (FFR) and FFR derived from computed tomography for functional assessment of coronary artery disease

BACKGROUND

Coronary computed tomography-derived fractional flow reserve (CT-FFR) and intravascular ultrasound-derived fractional flow reserve (IVUS-FFR) are two functional assessment methods for coronary stenoses. However, the calculation algorithms for these methods differ significantly. This study aimed to compare the diagnostic performance of CT-FFR and IVUS-FFR using invasive fractional flow reserve (FFR) as the reference standard.

METHODS

Six hundred and seventy patients (698 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2020 and July 2021. A total of 40 patients (41 lesions) underwent intravascular ultrasound (IVUS) and FFR evaluations within six months after completing coronary CT angiography were included. Two novel CFD-based models (AccuFFRct and AccuFFRivus) were used to compute the CT-FFR and IVUS-FFR values, respectively. The invasive FFR ≤ 0.80 was used as the reference standard for evaluating the diagnostic performance of CT-FFR and IVUS-FFR.

RESULTS

Both AccuFFRivus and AccuFFRct demonstrated a strong correlation with invasive FFR (R = 0.7913, P < 0.0001; and R = 0.6296, P < 0.0001), and both methods showed good agreement with FFR. The area under the receiver operating characteristic curve was 0.960 (P < 0.001) for AccuFFRivus and 0.897 (P < 0.001) for AccuFFRct in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (96.6%), specificity (85.7%), and the Youden index (0.823) using the same cutoff value of 0.80 for AccuFFRivus. A good diagnostic performance (sensitivity 89.7%, specificity 85.7%, and Youden index 0.754) was also demonstrated by AccuFFRct.

CONCLUSIONS

AccuFFRivus, computed from IVUS images, exhibited a high diagnostic performance for detecting myocardial ischemia. It demonstrated better diagnostic power than AccuFFRct, and could serve as an accurate computational tool for ischemia diagnosis and assist in clinical decision-making.

Quantification and statistical analysis on the cranial vault morphology for Chinese children 3-10 years old

BACKGROUND AND OBJECTIVE

Head injury is the leading cause of fatalities and disabilities in children. Characterizing the variation in cranial size/shape and thickness during growth is important for developing finite element models of child heads and evaluating head injury risk at different ages. However, the quantitative morphological features of the cranial vault (size/shape and non-uniform thickness distribution) have not been accounted for in children aged between 3 and 10 years old (YO).

METHODS

Geometrically equivalent discrete points were identified on 42 head CT scans of 3-10 YO children by separation, curve dividing, and point fitting. Based on discrete points, the principal component analysis and regression (PCA&R) method was used to develop a statistical model of the cranial vault as a function of age and head circumference.

RESULTS

The ontogeny of three-dimensional cranial morphology and non-uniform thickness from 3 to 10 years of age was quantified and cranial vault morphologies for 3-10 YO children were generated in 1 year intervals.

CONCLUSIONS

The automatic method, the procedure of identifying discrete points from CT scans, and the developed quantitative cranial vault model are reliable and accurate.